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Table 2

Estimates and summary statistics derived from probability densities.

Point estimate zphoto 0zmaxz×p(zd)dz$\int_0^{{z_{max}}} z \times p(z\mid d){\rm{d}}z$
Cumulative density estimate F(z|d) 0zp(zd)dz$\int_0^z p \left( {z'\mid d} \right){\rm{d}}z'$
Instance-wise residual δ- (zphotozspec)|(1 + Zspec)
Bin-wise mean redshift residual δ<z> (< Zphoto >< Zspec >)/(1+ < Zspec >) (*)
MAD-based deviation σMAD (**) 1.4826 × Median |δz Median(δz)|
Probability integral transform (PIT) 0zspec p(zd)dz$\int_0^{{z_{{\rm{spec }}}}} p (z\mid d){\rm{d}}z$
1-Wasserstein distance with the one-hot label 0zspec F(zd)dz+zspec zmax|1F(zd)|dz$\int_0^{{z_{{\rm{spec }}}}} F (z\mid d){\rm{d}}z + \int_{{z_{{\rm{spec }}}}}^{{z_{\max }}} | 1 - F(z\mid d)|{\rm{d}}z$
Continuous ranked probability score (CRPS) 0zspecF(zd)2 dz+zspeczmax(1F(zd))2 dz$\int_0^{{z_{{\rm{spec }}}}} F {(z\mid d)^2}{\rm{d}}z + \int_{{z_{{\rm{spec }}}}}^{{z_{\max }}} {(1 - F(} z\mid d){)^2}{\rm{d}}z$
Cross-entropy with the one-hot label − log p(zspec|d)
Entropy 0zmaxp(zd)logp(zd)dz$ - \int_0^{{z_{\max }}} p (z\mid d)\log p(z\mid d){\rm{d}}z$
Standard deviation σ 0zmax(zzphoto)2p(zd)dz$\sqrt {\int_0^{{z_{\max }}} {{{\left( {z - {z_{photo}}} \right)}^2}} p(z\mid d){\rm{d}}z} $
Skewness 0zmax(zzphoto )3p(zd)dz/σ3$\int_0^{{z_{\max }}} {{{\left( {z - {z_{{\rm{photo }}}}} \right)}^3}} p(z\mid d){\rm{d}}z/{\sigma ^3}$
Kurtosis 0zmax(zzphoto )4p(zd)dz/σ4$\int_0^{{z_{\max }}} {{{\left( {z - {z_{{\rm{photo }}}}} \right)}^4}} p(z\mid d){\rm{d}}z/{\sigma ^4}$

Notes.(*) <> denotes the mean computed in a redshift or magnitude bin.(**) MAD stands for the median absolute deviation.

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